要成為一位優秀的研究人員,首要具備獨立思考的能力, 統計學這門課協助妳/你擁有量化研究之專業能力,藉由專業的統計方法和知識,將數據轉換為有用的資訊,探討日常生活中無所不在的統計,以及如何正確使用統計,並利用統計進行決策判斷,在龐大的資料流中,有效率的進行有用資料之探勘和採礦,並在統計學的學習過程中逐漸培養妳/你的國際觀和思考判斷等競爭力.To become an excellent researcher, the first thing to do is to have the ability to think independently. This course in statistic helps you/you have the professional ability to quantitative research, convert data into useful information through professional statistic methods and knowledge, explore the statistic that is not present in daily life, and how to use statistic correctly. Measure and use the statistics to make decisions and judgments, efficiently conduct useful data exploration and mining in a large data stream, and gradually cultivate your/your international viewing and thinking judgment competition in the learning process of statistics.
統計方法是現今計量科學研究中最常用的方法之一，但是，隨著科技的進步、套裝軟體的發達，同學可以很容易的處理一些基本資料的分析及推論，但並不全然了解方法背後之理論基礎。因此，本課程的主要目的是建立同學能獲正確的統計基本概念。盡量以簡單、生動且易於了解的方式講授課程內容進而引發同學學習之興趣，避免艱深的內容和太多的數學推導。本課程內容包含：
1. 敘述統計：關於數據資料的描述及整理。
2. 機率論：統計推論的基礎。
3. 假設檢定。
4. 變方分析與實驗設計。
5. 迴歸分析。
Statistical methods are one of the most commonly used methods in today's quantitative scientific research. However, with the advancement of technology and the development of packaged software, students can easily handle the analysis and recommendation of some basic data, but they do not fully understand the theoretical basis behind the method. Therefore, the main purpose of this course is to establish the basic statistical concepts that students can obtain correctly. As much as possible, teach the course content in a simple, vivid and easy to understand way to attract students' interest in learning, avoiding deep content and too much mathematical guidance. The course includes:
1. Statistics: Description and sorting of data.
2. Opportunity theory: the basis of statistical recommendation.
3. Assume confirmation.
4. Change analysis and experimental design.
5. Reply analysis.
1. Newbold, P., Carlson, W., and Thorne, B.M., C.(2013), Statistics for Business and Economics, 8th edition, Pearson Education, Inc. （滄海圖書代理）(Textbook)
2. Slaughter, S.J. and Delwiche, L.D., 蔡宏明、蔡秉諺譯（2011年11月），SAS Enterprise Guide實用工具書，梅霖文化事業有限公司 (ISBN: 978-986-6511-58-5)
3. 曾淑峰、林志弘、翁玉麟（2012年9月），資料採礦應用—以SAS Enterprise Miner為工具，梅霖文化事業有限公司 (ISBN: 978-986-6511-60-8)
1. Newbold, P., Carlson, W., and Thorne, B.M., C. (2013), Statistics for Business and Economics, 8th edition, Pearson Education, Inc. (Textbook)
2. Slaughter, S.J. and Delwiche, L.D., Cai Hongming and Cai Bing-san (November 2011), SAS Enterprise Guide practical tools book, Meilin Cultural Affairs Co., Ltd. (ISBN: 978-986-6511-58-5)
3. Zeng Shufeng, Lin Zhihong, Weng Yulin (September 2012), data mining application—using SAS Enterprise Miner as a tool, Meilin Culture Industry Co., Ltd. (ISBN: 978-986-6511-60-8)
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 期中考期中考 Midterm exam |
30 | 筆試進行+PPT口頭報告 |
| 期末考期末考 Final exam |
30 | 筆試進行+書面報告 |
| 平時成績平時成績 Regular achievements |
40 | 包括學習態度(出缺席), 作業, 分組報告, 課堂成績和平時考試 |
